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Interactive collaborative filtering

Zhao, X; Zhang, W; Wang, J; (2013) Interactive collaborative filtering. In: Proceedings of the 22nd ACM international conference on Conference on information & knowledge management. (pp. 1411 - 1420). ACM: New York, NY, USA. Green open access

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Abstract

In this paper, we study collaborative filtering (CF) in an interactive setting, in which a recommender system continuously recommends items to individual users and receives interactive feedback. Whilst users enjoy sequential recommendations, the recommendation predictions are constantly refined using up-to-date feedback on the recommended items. Bringing the interactive mechanism back to the CF process is fundamental because the ultimate goal for a rec-ommender system is about the discovery of interesting items for individual users and yet users' personal preferences and contexts evolve over time during the interactions with the system. This requires us not to distinguish between the stages of collecting information to construct the user profile and making recommendations, but to seamlessly integrate these stages together during the interactive process, with the goal of maximizing the overall recommendation accuracy throughout the interactions. This mechanism naturally addresses the cold-start problem as any user can immediately receive sequential recommendations without providing ratings beforehand. We formulate the interactive CF with the probabilistic matrix factorization (PMF) framework, and leverage several exploitation-exploration algorithms to select items, including the empirical Thompson sampling and upper confidence bound based algorithms. We conduct our experiment on cold-start users as well as warm-start users with drifting taste. Results show that the proposed methods have significant improvements over several strong baselines for the MovieLens, EachMovie and Netflix datasets. Copyright 2013 ACM.

Type: Proceedings paper
Title: Interactive collaborative filtering
Event: CIKM '13
ISBN-13: 978-1-4503-2263-8
Open access status: An open access version is available from UCL Discovery
DOI: 10.1145/2505515.2505690
Publisher version: http://dx.doi.org/10.1145/2505515.2505690
Language: English
Additional information: "© ACM 2013. This is the author's version of the work. It is posted here for your personal use. Not for redistribution. The definitive Version of Record was published in Proceedings of the 22nd ACM international conference on Conference on information & knowledge management, http://dx.doi.org/10.1145/2505515.2505690."
UCL classification: UCL
UCL > Provost and Vice Provost Offices
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science
URI: https://discovery.ucl.ac.uk/id/eprint/1401363
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